Scenario: Big Picture

You are a business intelligence manager. Your employees rely on your business intelligence service being online with the latest data when they arrive at work in the morning. You need to know if something went wrong with the overnight processes — before everyone gets to work. What you need is a dashboard you can look at each morning that shows you what, if anything, is holding up your server. If anything’s going wrong, you can jump directly to that process and take corrective action. Also, you can delve into that process’s recent history to see if it’s been consistently problematic. If it has, you need to do more research and decide on a course of action to fix the process. To determine what to do next, you might ask the following questions:

Did our server processes succeed today?

Which processes failed?

Are the failing processes repeatedly failing?

Which processes are taking longer than usual?

Specifics

You manage a server and need to respond quickly if processes fail. If these processes are going to cause problems for the users, those problems need to be identified and addressed quickly.

You need an email each morning with a summary report of overnight processes. If a high number fail or if some key processes fail, you need to click the email to go to the live dashboard and drill into the details.

For any given failed process, you need extra contextual details to help you diagnose and fix the problem. Was this failure caused by a problem earlier in the process chain? Is this process consistently failing?

Related Scenarios

You are a manufacturer and need to track the production schedule’s progress towards completion.

You are an event manager and need to track that tasks begin correctly and run to time.

How People Use the Dashboard

As an administrator responsible for keeping your enterprise’s systems up and running, you need to know if things are going wrong. A static image of the dashboard is emailed to Mark Jackson, the dashboard designer, each morning. The bar chart at the top shows percentage of failures for each of the last 14 days. The most recent is at the far right (the highlighted bar in the overview dashboard). Comparing last night to the last two weeks allows Mark to easily see if last night was normal or an outlier. The average failure rate is shown as a dotted line.

Mark can see that 6.7 percent of processes failed overnight. That’s a real problem, and significantly above the average failures for the previous 14 days. Some investigation is needed.

Mark can see all the processes that took place that day. Gray ones succeeded, and red ones failed. Reference lines on each Gantt bar show the scheduled start time (dotted line) and the average time the task has taken(solid line). The Epic Radiant Orders task is the clear problem on this day.

The Big Book of Dashboards

Figure 18.1: The tool tip adds extra detail about the failure.

If Mark wants to investigate any task in detail, he can hover over it to see a tool tip for extra contextual information. (See Figure 18.1.)

Now Mark can see details about the Epic Radiant Orders task. Not only did the task fail, it took nearly seven hours to fail. On average, it takes around two hours to complete.

From here, he has two options. The tool tip has a URL link in it: He can click the link in the tool tip to go and see the task on the server itself. His other option is to click on the Gantt bar, which reveals a new view at the bottom of the dashboard showing detail for the task.

In Figure 18.2, Mark can see that the Epic Radiant Orders task has been failing consistently recently.

Whatever preventive medicine he has been applying has not yet succeeded.

The detail view shows the performance of a single task over the previous month. Clearly the Epic Radiant Orders task needs some investigation. It’s failed seven times in the last month.

Throughout this process, Mark has gone from receiving an email with a daily alert to being able to see the overview for the day. From there, he can drill down in to detail where he needs to explore further and finally go straight to any server processes that need investigation.

The Big Book of Dashboards

Figure 18.2: Detail view for a specific task. In this case, we are looking at the Epic Radiant Orders task.

Slideshows

Selling beyond the CIO – How partners can influence the new breed of tech buyers

This ARN Roundtable, in association with Oracle, highlighted the emergence of a new breed of technology buyer, assessing how partners can engage outside of IT, and the skills required to sell across new business units.

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